ciAUC.rocit: Confidence Interval of AUC

In ROCit: Performance Assessment of Binary Classifier with Visualization

Description

ciAUC constructs confidence interval of area under curve (AUC) of receiver operating characteristic (ROC) curve. This is an S3 method defined for object of class "rocit".

Usage

## S3 method for class 'rocit'
ciAUC(
  object,
  level = 0.95,
  delong = FALSE,
  logit = FALSE,
  nboot = NULL,
  step = FALSE,
  ... = NULL
)

Arguments

object	An object of class "rocit", returned by rocit.
level	Level of confidence, must be within the range (0 1). Default is 0.95.
delong	Logical; indicates whether DeLong formula should be used to estimate the variance of AUC. Default is FALSE.
logit	Logical; indicates whether confidence interval of logit transformed AUC should be evaluated first. Default is FALSE
nboot	Number of bootstrap samples, if bootstrap method is desired. Default is NULL. If a numeric value is specified, overrides logit and delong arguments.
step	Logical, default in FALSE. See rocit.
...	NULL. Used for S3 generic/method consistency.

Value

An object of class "rocitaucci".

See Also

rocit, ciROC.rocit

Examples

data("Diabetes")
logistic.model <- glm(as.factor(dtest)~chol+age+bmi,
                      data = Diabetes,family = "binomial")
score <- logistic.model$fitted.values
class <- logistic.model$y
# Make the rocit objects
rocit_bin <- rocit(score = score, class = class, method = "bin")
# Confidence interval of AUC
ciAUC(rocit_bin, level = 0.9)
ciAUC(rocit_bin, delong = TRUE, logit = TRUE)

ROCit documentation built on July 1, 2020, 11:28 p.m.